{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cifar10数据集包含飞机、汽车、鸟、猫、鹿、狗、青蛙、马、船、卡车共10个类别"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.keras import layers\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 加载数据集\n",
    "(x_train, y_train),(x_test, y_test) = tf.keras.datasets.cifar10.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50000\n",
      "10000\n",
      "(50000, 32, 32, 3)\n"
     ]
    }
   ],
   "source": [
    "# 查看图片数量和大小。因为这里的图像已经是彩色图像了，因此第四维的值为3\n",
    "print(len(x_train))\n",
    "print(len(x_test))\n",
    "print(x_train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([59, 62, 63], dtype=uint8)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看图片单个点信息。因为是彩色图片，所以单个点的信息包含R、G、B三个颜色通道的值\n",
    "# 第一个[0]代表取50000张图片中的第一张，第二个[0]代表取第一行，第三个[0]代表取第一列\n",
    "x_train[0][0][0] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义数字对应类别的字典，因为我们训练时的标签是0-9，要映射成对应的类别名称显示\n",
    "label_dict = {0:'airplane',1:'automobile',2:'bird',3:'cat',4:'deer',5:'dog',6:'frog',7:'horse',8:'ship',9:'truck'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1008 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 定义显示图片函数并显示图片，该函数和第一节大体一样，有小部分需要修改一下\n",
    "def plot_images_labels_prediction(images, labels, prediction, idx, num=10):\n",
    "    fig = plt.gcf()\n",
    "    fig.set_size_inches(12, 14)\n",
    "    if num > 25: \n",
    "        num = 25\n",
    "    for i in range(0, num):\n",
    "        ax = plt.subplot(5, 5, i + 1)\n",
    "        ax.imshow(images[idx], cmap='binary') \n",
    "        title= str(i) + ' ' + label_dict[labels[i][0]]  # 显示数字对应的类别\n",
    "        if len(prediction) > 0:\n",
    "            title += '=>' + label_dict[prediction[i]]  # 显示数字对应的类别\n",
    "        ax.set_title(title,fontsize=10)\n",
    "        ax.set_xticks([])\n",
    "        ax.set_yticks([])\n",
    "        idx += 1\n",
    "    plt.show()\n",
    "\n",
    "plot_images_labels_prediction(x_train, y_train, [], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.23137255 0.24313726 0.24705882]\n"
     ]
    }
   ],
   "source": [
    "# 数据标准化并查看一个点的值\n",
    "x_train_normalize = x_train.astype('float32') / 255\n",
    "x_test_normalize = x_test.astype('float32') / 255\n",
    "print(x_train_normalize[0][0][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 对标签进行One-Hot（独热编码）\n",
    "y_train_OneHot = tf.keras.utils.to_categorical(y_train)\n",
    "y_test_OneHot = tf.keras.utils.to_categorical(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 模型搭建，这里搭建3层卷积神经网络提取特征\n",
    "model = tf.keras.models.Sequential()\n",
    "model.add(layers.Conv2D(filters=32,kernel_size=(3,3),padding='same',input_shape=(32,32,3),activation='relu'))\n",
    "model.add(layers.Dropout(0.3))\n",
    "model.add(layers.Conv2D(filters=32,kernel_size=(3,3),padding='same',activation='relu'))\n",
    "model.add(layers.MaxPooling2D(pool_size=(2,2)))\n",
    "model.add(layers.Conv2D(filters=64,kernel_size=(3,3),activation='relu',padding='same'))\n",
    "model.add(layers.Dropout(0.3))\n",
    "model.add(layers.Conv2D(filters=64,kernel_size=(3,3),padding='same',activation='relu'))\n",
    "model.add(layers.MaxPooling2D(pool_size=(2,2)))\n",
    "model.add(layers.Conv2D(filters=128,kernel_size=(3,3),activation='relu',padding='same'))\n",
    "model.add(layers.Dropout(0.3))\n",
    "model.add(layers.Conv2D(filters=128,kernel_size=(3,3),padding='same',activation='relu'))\n",
    "model.add(layers.MaxPooling2D(pool_size=(2,2)))\n",
    "model.add(layers.Flatten())\n",
    "model.add(layers.Dropout(0.3))\n",
    "model.add(layers.Dense(2500, activation='relu'))\n",
    "model.add(layers.Dropout(0.3))\n",
    "model.add(layers.Dense(1500, activation='relu'))\n",
    "model.add(layers.Dropout(0.3))\n",
    "model.add(layers.Dense(10, activation='softmax'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 模型参数设置\n",
    "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n",
      "313/313 [==============================] - 208s 663ms/step - loss: 1.8398 - accuracy: 0.3113 - val_loss: 1.9757 - val_accuracy: 0.3216\n",
      "Epoch 2/5\n",
      "313/313 [==============================] - 180s 577ms/step - loss: 1.4093 - accuracy: 0.4825 - val_loss: 1.3845 - val_accuracy: 0.5080\n",
      "Epoch 3/5\n",
      "313/313 [==============================] - 179s 572ms/step - loss: 1.1898 - accuracy: 0.5705 - val_loss: 1.1076 - val_accuracy: 0.6080\n",
      "Epoch 4/5\n",
      "313/313 [==============================] - 179s 571ms/step - loss: 1.0532 - accuracy: 0.6255 - val_loss: 1.0587 - val_accuracy: 0.6258\n",
      "Epoch 5/5\n",
      "313/313 [==============================] - 179s 573ms/step - loss: 0.9476 - accuracy: 0.6643 - val_loss: 0.8966 - val_accuracy: 0.6815\n"
     ]
    }
   ],
   "source": [
    "# 模型训练\n",
    "train_history = model.fit(x_train_normalize, y_train_OneHot, validation_split=0.2, epochs=5, batch_size=128, verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 定义曲线显示函数并显示\n",
    "def show_train_history(train_history, train, validation):\n",
    "    plt.plot(train_history.history[train])\n",
    "    plt.plot(train_history.history[validation])\n",
    "    plt.title('Train History')\n",
    "    plt.xlabel('epoch')\n",
    "    plt.ylabel(train)\n",
    "    plt.legend(['train','validation'],loc='upper left')\n",
    "\n",
    "show_train_history(train_history, 'accuracy', 'val_accuracy')\n",
    "show_train_history(train_history, 'loss', 'val_loss')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "313/313 - 11s - loss: 0.9006 - accuracy: 0.6785\n",
      "0.6784999966621399\n"
     ]
    }
   ],
   "source": [
    "# 测试机进行测试\n",
    "scores = model.evaluate(x_test_normalize, y_test_OneHot, verbose=2)\n",
    "print(scores[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-15-e93e8c988dcf>:2: Sequential.predict_classes (from tensorflow.python.keras.engine.sequential) is deprecated and will be removed after 2021-01-01.\n",
      "Instructions for updating:\n",
      "Please use instead:* `np.argmax(model.predict(x), axis=-1)`,   if your model does multi-class classification   (e.g. if it uses a `softmax` last-layer activation).* `(model.predict(x) > 0.5).astype(\"int32\")`,   if your model does binary classification   (e.g. if it uses a `sigmoid` last-layer activation).\n",
      "[3 8 8 ... 5 1 7]\n"
     ]
    }
   ],
   "source": [
    "# 模型预测\n",
    "prediction = model.predict_classes(x_test_normalize)\n",
    "print(prediction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1008 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 调用之前定义的plot_images_labels_prediction函数查看具体图片信息和结果\n",
    "plot_images_labels_prediction(x_test, y_test, prediction, 0, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.00104498 0.00142254 0.0065442  0.8444942  0.00554028 0.10688003\n",
      " 0.01496903 0.00609455 0.01192717 0.00108293]\n"
     ]
    }
   ],
   "source": [
    "# keras的model.predict_classes是用于直接预测出类别结果，\n",
    "# 如果我们想知道预测图片分别对应10个类别的概率，我们可以用model.predict来进行查看\n",
    "prediction_probability = model.predict(x_test_normalize)\n",
    "print(prediction_probability[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 我们可以定义一个展示图片 + 预测概率的函数，方便查看预测概率结果\n",
    "def show_predicted_probability(x, y, prediction, prediction_probability, i):\n",
    "    print(\"label:\", label_dict[y[i][0]], 'predict,', label_dict[prediction[i]])\n",
    "    plt.figure(figsize=(2, 2))\n",
    "    plt.imshow(x[i])\n",
    "    plt.show()\n",
    "    for j in range(10):  # 输出10个类别概率\n",
    "        print(label_dict[j] + 'Probability:%1.9f' % (prediction_probability[i][j]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 模型的保存\n",
    "model.save_weights(\"cifar.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 如果要加载一个已经训练好的模型的参数，则用load_weights进行读取\n",
    "model.load_weights(\"cifar.h5\")"
   ]
  }
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